14results about How to "Solve conflicts" patented technology

This application provides an AI-based camera control method, device, and storage medium, relating to the field of intelligent monitoring. It solves the technical problems of resource competition and conflict during multi-camera collaborative tracking, and low monitoring efficiency due to a single control strategy. The method includes: acquiring the current state information of at least two cameras within a target monitoring area, and the motion trajectory of at least one target object within the field of view of the at least two cameras; constructing a conflict detection model based on historical current state information and motion trajectories; identifying camera combinations with tracking competition within the target monitoring area as game participants based on the conflict detection model; constructing a multi-objective optimization-based payoff factor for the game participants; determining the optimal control strategy combination based on the payoff factor, and sending control operation commands. This application can improve the overall efficiency and intelligence level of the monitoring system.

The invention relates to the technical field of diabetic nephropathy onset risk, in particular to an onset risk prediction method and system for type 2 diabetic nephropathy, and the method comprises the following steps: screening characteristic factors through multi-factor Logistic regression, and obtaining contribution degree through principal component analysis; information centralization and decentralization feature weights are constructed based on the contribution degree, and the game theory is introduced for fusion to obtain the optimal feature weight; and finally, inputting the weighted features into the attention guidance double-current time sequence static fusion network which is deeply fused with the optimal weight, and outputting an onset risk. According to the method, contributions of core and secondary indexes are balanced through the game theory, and deep association of static and dynamic data is mined by using a double-flow network, so that the prediction accuracy is remarkably improved.

This application provides a method and system for persistent PCI device addresses in a virtualized environment. The method involves creating an address inheritance QoS policy for the device to be persisted, writing PCI address metadata, and adding a minimum bandwidth rule to bind NUMA nodes and physical network cards. The scheduler reserves the corresponding PCI address slot according to this rule, reads the metadata, and restores the PCI address in the reserved slot, thus achieving address persistence. This application reuses the platform's native QoS policy capabilities without modifying the core architecture, enabling cross-virtual machine PCI address inheritance, avoiding address conflicts, ensuring the stable operation of services relying on fixed PCI addresses, and adapting to large-scale cloud environment deployments.

This application provides a display device and a method for controlling audio playback during multi-channel projection. The method records the terminal devices that establish projection connections with the display device based on a projection list, as well as the connection order between the terminal devices and the display device. When the display device establishes projection connections with at least two terminal devices, the audio modes of the multi-channel projection are adjusted through the projection list. One terminal device in the projection list is set to a non-mute mode, while the other terminal devices are set to mute mode, thus allowing the display device to play only the audio from one projection channel. This method allows for dynamic audio settings based on different projection scenarios and dynamic audio control based on user selection, resolving audio conflicts during multi-channel projection.

This application discloses a multi-label classification method and related apparatus. The method includes: inputting data to be classified into a multi-label classification model; outputting a target category prediction result based on the data to be classified through a category prediction layer in the multi-label classification model; and outputting a target mutual exclusion group prediction result based on the target category prediction result through a mutual exclusion group prediction layer in the multi-label classification model; correcting the target category prediction result based on the mutual exclusion group prediction result to obtain the target multi-label classification result corresponding to the data to be classified. This method not only enables the mutual exclusion group prediction to more accurately capture the logical relationship between label categories, avoiding misjudgment of mutual exclusion relationships caused by independently using the original features of the data to be classified, thus improving the reliability of model prediction, but also effectively eliminates logical conflicts in the target category prediction results, avoiding the contradiction of simultaneous occurrence of mutually exclusive label categories, and obtaining a target multi-label classification result that better conforms to actual business logic, thereby improving the accuracy of multi-label classification.

The application provides a heuristic-based cell PCI planning method and system, relates to the technical field of PCI distribution and planning in a mobile communication network, and comprises the steps of multi-objective optimization model establishment, data acquisition and initialization, initial distribution, problem decomposition, parallel optimization and the like. Through the construction of an accurate multi-objective optimization model and the design of an efficient decomposition-parallel system solution framework, and in combination with a heuristic algorithm for quickly generating an initial feasible solution, a cell interaction graph model constructed based on each cell and its neighboring relationship data is segmented by using a graph segmentation algorithm, the multi-objective optimization problem is decomposed into multiple sub-optimization problems and solved by using a multi-objective evolutionary algorithm, the conflict and interference problems among neighboring cells can be effectively solved, the global optimization conflict, confusion and modulo 3 interference are solved while ensuring the solution efficiency and coping with a super-large-scale network, and finally a high-quality globally optimized PCI planning scheme is output, so that the overall network performance and user experience are improved.

The application discloses a process chamber, an upper electrode device thereof and a semiconductor process equipment. The upper electrode device comprises a radio frequency coil (11) and an adjustable capacitor (12). The radio frequency coil (11) is used for being wound outside a shielding cylinder (70) of the process chamber, and the shielding cylinder (70) is used for being sleeved outside a plasma generating cavity (20) of the process chamber. The adjustable capacitor (12) is connected in series with the radio frequency coil (11), and the adjustable capacitor (12) is used for being adjusted to different capacitance values in an ignition stage and a reaction stage of the process chamber. The above scheme can solve the problems of ignition difficulty and plasma bombardment on a dielectric window, and can also relieve the problem of abnormal discharge caused by the adoption of a lifting structure of the radio frequency coil.

This invention relates to the field of coal mine gas geological disaster prevention and intelligent identification technology, and discloses a method and system for intelligent identification and graded early warning of underground gas geological anomalies in coal mines. The method includes: S1, collecting multi-source heterogeneous monitoring data in the target area of ​​the coal mine and performing standardization processing and spatiotemporal benchmark unification; S2, constructing a multi-dimensional feature fingerprint database based on historical or accumulated standardized datasets; S3, acquiring real-time multi-source monitoring data for the current tunneling or exploration process and extracting its features; based on the multi-dimensional feature fingerprint database, using evidence theory to fuse and calculate multiple extracted real-time feature evidences to obtain a comprehensive confidence assessment result for the existence of a specific type of gas geological anomaly in the undiscovered area ahead; S4, generating graded early warning information based on the comprehensive confidence assessment result and a preset risk level threshold. This invention achieves advanced identification, risk assessment, and targeted early warning of geological disasters such as underground gas outbursts.

This invention relates to the fields of new energy power generation and electric vehicle charging technology, and particularly to a V2G bidirectional energy management system and method for distributed wind, solar, and energy storage charging pile clusters, comprising: a central dispatch server and multiple edge control nodes. A data acquisition and prediction module generates predicted data; a global optimization module generates and issues day-ahead global power commands based on this data; a local real-time control module generates and executes real-time power adjustment commands based on model predictive control, targeting the tracking commands; a communication monitoring and switching module switches to a network outage mode during communication interruptions, independently controls and caches data based on a local rule base; a network outage resumption and synchronization module uploads cached data and synchronizes key states through a consensus algorithm after communication is restored; a data fusion and recovery module performs data fusion and verification based on a global timestamp, updates the global database, and issues confirmation commands. This invention achieves autonomous operation during communication interruptions and data consistency after recovery.

This application discloses a hierarchical adaptive intelligent association and alignment method for multimodal flight data, comprising: acquiring multi-source airborne flight data and preprocessing it; mapping data of different modes in the preprocessed multi-source airborne flight data to a common feature space to obtain cross-modal alignment features, wherein an aircraft physical dynamic model is introduced as a constraint during the mapping process; performing local precise association and global semantic association in parallel based on the cross-modal alignment features; wherein the local precise association is used to obtain pixel-level or point-level matching results, and the global semantic association is used to obtain globally consistent semantic association results; and fusing the results of the local precise association and the global semantic association to obtain association information of corresponding granularity. This invention effectively solves the "data silo" problem caused by differences in format, spatiotemporal reference, and modality of multi-source flight data, significantly improving association accuracy, robustness, and system adaptability.

Embodiments of the application disclose a micro application running method and device, equipment, storage medium and program product, and belong to the technical field of application. The method comprises the following steps: obtaining a target micro application script of a target micro application; in response to a target trigger event, triggering a target trigger corresponding to the target trigger event in the target micro application script; reading an event parameter corresponding to the target trigger event from a first data storage area, different triggers corresponding to different first data storage areas; and based on the event parameter, executing a target call action corresponding to the target trigger. In the micro application running process, different triggers are provided with special data storage areas, so that the call action associated with the trigger can access the data storage area, which can achieve the purpose of data transmission in the micro application, and can also avoid the conflict problem of data corresponding to different triggers.

This application discloses a novel algorithm for constructing a genetic map of a MAGIC population, comprising: collecting species data; segmenting chromosomes based on the collected data to form chromosome fragments; calculating the parental genetic similarity index of chromosome fragments to determine parental origin; obtaining a definite origin matrix and a fuzzy origin matrix; using definite fragments from a single parental origin in the definite origin matrix as anchor points; using the anchor points as starting points, examining adjacent fragments of fuzzy fragments in the fuzzy origin matrix to determine parental origin; merging fragments with the same parental origin and adjacent positions into a larger fragment to form a parental origin matrix; calculating recombination rate and genetic distance; constructing a genetic map; and using the novel algorithm to analyze the whole-genome resequencing data of a MAGIC population of a specified crop, thereby effectively detecting minor genes controlling complex quantitative traits, clarifying the parental origin of each variation site, and finding the required high-quality parents, thereby improving the breeding process.

This patent discloses a convolutional neural network processing method and apparatus, belonging to the field of convolutional neural networks, used to improve data transmission efficiency, optimize the computation process of deep learning, increase computation speed, and reduce power consumption. The main technical solution of this invention is as follows: Weight data is input to a multiplier array according to a first preset method; based on the channels corresponding to each weight data in each row of multipliers, a sub-feature data set corresponding to each row of multipliers is determined; based on the sub-feature data set corresponding to each row of multipliers, the sub-feature data set is input to the multiplier array; the weight data in each multiplier of any row of multipliers is multiplied by each element feature data in the sub-feature data set corresponding to that row of multipliers to obtain a first set of dot product results; the obtained first set of dot product results is input to an accumulator for accumulation; in response to the completion of the accumulator accumulation, the processing result corresponding to the feature data set to be processed is obtained.

The application belongs to the field of mobile robot path planning and tracking control, and specifically relates to a kind of autonomous navigation method for complex dynamic environment-oriented car-like mobile robot. The method comprises the following steps: 1) generating an initial trajectory by A* search algorithm, limiting the trajectory range by using the self-vehicle expansion plane, iteratively optimizing the coordination point and expansion plane, and dynamically adjusting the path to complete path planning; 2) generating a globally smooth path by using virtual chassis and pure pursuit control, iteratively optimizing the path sampling and conflict detection, dynamically adjusting the local path segment, and realizing tracking control. The application optimizes the path planning and tracking control method, improves the adaptability of the robot to complex environment, realizes real-time path adjustment and conflict-free navigation, and ensures that the mobile robot safely and efficiently completes the task.